Abstract

Info

Title:: Noise elimination methods for fibre tracking in diffusion tensor imaging

Author(s):: PAN Yunda1; XU Longchun2; HE Lemin1; ZHANG Minfeng2; ZHANG Gang2; ZOU Yue2; ZHAO Wenbo2; SONG Xuerui1; DUAN Luowei1; ZHANG Guangyu1; 1. College of Radiology, Taishan Medical University, Tai’an 271016, China; 2. Affiliation Hospital of Taishan Medical University, Tai’an 271000, China

Keywords:: ; Keywords: diffusion tensor imaging; median filter; Gaussian smoothing filter; maximum-minimum filter; mixed filter; fibre tracking; noise elimination method

Abstract:: Abstract: Several noise elimination approaches for fibre tracking in diffusion tensor imaging (DTI) are analyzed. The simulation results indicate that Gaussian smoothing filter, median filter, and maximum-minimum filter are able to eliminate the noise in DTI image. Gaussian smoothing filter eliminates high-frequency white noise, but causes fuzzy edges of images and affects the connectivity of DTI fibre tracking. Median filter not only eliminates random noise, but also remains valuable information, which improves the effect of DTI fibre tracking. Maximum-minimum filter inhibits the effects of significant noise and improves the connectivity of DTI fibre tracking. Herein a mixed filtering method by integrating maximum-minimum filter with median filter is proposed for image denoising. The proposed method is proved to be able to effectively reduce the effects of noise on DTI fibre tracking, achieving better DTI fibre tracking results.